dpnp.cosh

dpnp.cosh(x, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Computes the hyperbolic cosine for each element \(x_i\) for input array x.

The mathematical definition of the hyperbolic cosine is

\[\operatorname{cosh}(x) = \frac{e^x + e^{-x}}{2}\]

For full documentation refer to numpy.cosh.

Parameters:

  • x ({dpnp.ndarray, usm_ndarray}) -- Input array, expected to have a floating-point data type.

  • out ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array to populate. Array must have the correct shape and the expected data type.

    Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) --

    Memory layout of the newly output array, if parameter out is None.

    Default: "K".

Returns:

out -- An array containing the element-wise hyperbolic cosine. The data type of the returned array is determined by the Type Promotion Rules.

Return type:

dpnp.ndarray

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.acosh

Hyperbolic inverse cosine, element-wise.

dpnp.sinh

Hyperbolic sine, element-wise.

dpnp.tanh

Hyperbolic tangent, element-wise.

dpnp.cos

Trigonometric cosine, element-wise.

Examples

>>> import dpnp as np
>>> x = np.array([0, np.pi/2, np.pi])
>>> np.cosh(x)
array([1.0, 2.5091786, 11.591953])